Research on Data Mining of Intelligent Education Evaluation from the Perspective of the Knowledge Graph

Abstract

The continuous development of Internet information technology given birth to data mining technology. Data mining is applied to analyze the internal relationships of data and provides a more optimized advancement way. The paper focuses on how to improve the data mining and analysis capabilities of intelligent education to associate students of the same characteristics. A cluster analysis method was utilized to construct a students' knowledge graph model, which used a text classification algorithm to classify the evaluation questions and attribute them into various knowledge points. On the basis of the analysis on the data generated from online education, the clustering algorithm was adopted to classify the learning characteristics of the students. A knowledge graph developed by associating the students with similar characteristics was visualized be means of information technology in order to realize visualized and intelligent teaching.